Genomic Activation of PPARG Reveals a Candidate Therapeutic Axis in Bladder Cancer

Home , Gene knockout, Rosiglitazone

Author Manuscript Published OnlineFirst on September 18, 2017; DOI: 10.1158/0008-5472.CAN-17-1701 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

RXRA and PPARG in Bladder Cancer

Genomic activation of PPARG reveals a candidate therapeutic axis in bladder cancer

Jonathan T. Goldstein1, Ashton C. Berger1, Juliann Shih1, Fujiko F. Duke1, Laura Furst1, David J. Kwiatkowski2, Andrew D. Cherniack1,3, Matthew Meyerson1,3,4,5 and Craig A. Strathdee1 Affiliations: 1The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America. 2Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 3Department of Medical Oncology, Dana- Farber Cancer Institute, Boston, Massachusetts, United States of America, 4Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America. 5Department of Pathology, Harvard Medical School, Boston, Massachusetts, United States of America. Current address for F. Duke: Gritstone Oncology, Cambridge, MA USA.

Running title: RXRA and PPARG in bladder cancer Keywords: RXRA, PPARG, Genitourinary cancers: bladder, Nuclear receptors: structure and function

Additional information. Financial support: Financial support for this work was provided by Bayer AG (Berlin, Germany) (J.Goldstein, A.Berger, J.Shih, F.Duke, L.Furst, A.Cherniack, M.Meyerson, and C.Strathdee) and the National Cancer Institute under grant 5R35CA197568-02 (M. Meyerson). Corresponding Author: Matthew Meyerson, Dana-Farber Cancer Institute, Boston, MA, 02115, USA; Tel: 617-632-4768, Email: [email protected] Conflict of interest disclosure statement; The Broad Institute and Dana-Farber Cancer Institute have filed a patent application for aspects of the work described in this paper. Financial support for this work was provided by Bayer AG (Berlin, Germany). M. Meyerson is a member of the Scientific Advisory Board and equity holder of Origimed. 1

Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2017 American Association for Cancer Research. Author Manuscript Published OnlineFirst on September 18, 2017; DOI: 10.1158/0008-5472.CAN-17-1701 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

RXRA and PPARG in Bladder Cancer

Abstract The PPARG gene encoding the nuclear receptor PPAR-gamma is activated

in bladder cancer, either directly by gene amplification or mutation, or indirectly

by mutation of the RXRA gene which encodes the heterodimeric partner of

PPAR-gamma. Here we show that activating alterations of PPARG or RXRA

lead to a specific gene expression signature in bladder cancers. Reducing

PPARG activity, whether by pharmacologic inhibition or genetic ablation,

inhibited proliferation of PPARG-activated bladder cancer cells. Our results

offer a preclinical proof of concept for PPARG as a candidate therapeutic target

in bladder cancer.

RXRA and PPARG in Bladder Cancer

Introduction

Bladder cancer is the fifth most commonly diagnosed cancer in the United

States with an annual incidence of 80,000 cases and an annual mortality of

15,000. Most patients are diagnosed with non-invasive/superficial urothelial

carcinoma of the bladder and respond well to transurethral resection, Bacillus

Calmette-Guérin (BCG) immunotherapy, and regular cystoscopic surveillance,

with a 5-year survival rate of 96%. Patients diagnosed with muscle-invasive

disease have a poorer prognosis, however, with a 5-year survival rate of 35-

70%, depending upon the extent of invasion, regional and systemic

metastases, and response to therapy.

Recently several immune checkpoint blockade drugs have been FDA-

approved for treatment of urothelial carcinoma, including atezolizumab, an anti-

PD-L1 antibody, in 2016 (1); nivolumab and pembrolizumab, anti-PD-1

antibodies, in 2017 (2) ; and avelumab and durvalumab, anti-PD-L1 antibodies,

in 2017 (3,4). These approvals mark the first new drugs for metastatic bladder

cancer in over 20 years. However, the objective response rates (defined using

RECIST v1.1) were relatively low in these clinical trials, with 15-20% overall

response rate and 26-28% response rate in PD-L1-positive patients (1,2).

Beyond checkpoint inhibitors, a number of therapies targeting specific genetic

alterations, including FGFR3 alterations, mTOR pathway alterations, and DNA

repair deficiencies associated with ERCC2 alterations (5-8), are under clinical

RXRA and PPARG in Bladder Cancer

evaluation.

We explored large-scale cancer genome datasets derived from patients with

muscle-invasive bladder cancer with the purpose of identifying novel

therapeutic targets. Hotspot mutations (p.S427F/Y) in the retinoid X receptor

alpha (RXRA) gene are present in ~5% of bladder cancer samples (9,10).

RXRA is a well characterized ligand-activated nuclear receptor that serves as a

requisite heterodimer partner for ~30 nuclear receptors, including PPARA,

PPARG, PPARD, RARA, RARB, VDR, TR, LXR, and PXR (11), suggesting that

recurrent mutations in RXRA could impact the formation and/or function of

these heterodimers and change the expression of their downstream target

genes. Previous reports have shown that cancer samples containing RXRA

p.S427F/Y mutations are associated with enhanced expression of genes

involved in adipogenesis and lipid metabolism, including ACOX1, ACSL1,

ACSL5, FABP4, and HMGS2 (9). These genes are targets of peroxisome

proliferator-activated receptor gamma (PPARG), a member of the PPAR

subfamily of nuclear receptors.

Interestingly, the PPARG gene is focally amplified in 15% of bladder cancer

samples (Supplementary Fig. 1A and (12)). This amplification is strongly

correlated with expression of PPARG (Supplementary Fig. 1B) as well as

expression of PPARG target genes and luminal differentiation markers such as

GATA3, UPK2, ACOX1, and UPK1A (Supplementary Fig. 1C and (13-16)).

PPARG is a master regulator of adipocyte differentiation and controls

RXRA and PPARG in Bladder Cancer

expression of a large set of genes involved in lipid and glucose homeostasis

(12). In contrast to PPARG’s well-characterized activity in adipocytes, however,

little is known about its function in the urinary bladder and in the pathogenesis

of bladder cancer.

The potential risk of bladder cancer upon activation of the PPAR subfamily

of nuclear receptors is controversial, and was first suggested following rodent

toxicity studies testing anti-diabetic PPAR agonists in which numerous glitazar-

class PPARA/PPARG dual agonist compounds were associated with an

increased incidence of bladder cancer (17). In terms of more selective PPARG

agonists, also anti-diabetic drugs with insulin sensitizing activity, the

carcinogenic effect in rodents was also observed with pioglitazone, which has

weak PPARA activity (18), but not with rosiglitazone, which is highly selective

for PPARG (17,19). In a more sensitive, chemically-induced model using the

carcinogen, 4-hydroxybutyl (butyl) nitrosamine (OH-BBN), rosiglitazone was

found to potentiate urinary bladder carcinogenesis in rats compared to OH-BBN

alone (20). It was originally hypothesized that the effects of PPARA/PPARG

dual agonists on promoting bladder cancer was rodent-specific due to indirectly

causing calcium crystal formation in the bladder resulting in urolithiasis (21).

Numerous studies have since examined the incidence of bladder cancer in

humans following the clinical use of these compounds, with some detecting an

increased risk and others concluding there is no increased risk (22,23). The

most comprehensive retrospective study to date showed an increase in the

RXRA and PPARG in Bladder Cancer

hazard ratio for bladder cancer with long-term, high-dose treatment with

pioglitazone (24).

Based on the combined genetic and pharmacologic evidence, we

hypothesized that activation of PPARG is oncogenic in the transitional epithelial

cells of the bladder. We evaluated this by investigating the biological impact of

ectopic expression of mutant alleles of RXRA and PPARG, pharmacologic

ablation of RXRA/PPARG signaling using small molecule perturbagens, and

genetic ablation of RXRA and PPARG using CRISPR/Cas9 gene knockouts.

Our results demonstrate an oncogenic role for PPARG in the development of

luminal bladder cancer, revealing a novel axis that could be exploited for the

development of targeted therapies for this disease.

RXRA and PPARG in Bladder Cancer

Materials and Methods

Chemicals

Rosiglitazone, pioglitazone, tesaglitazar, GW9662, T0070907, UVI3003 and

SR1664 were purchased from Tocris Bioscience (Minneapolis, MN). SR2595

and SR10221 were synthesized according to published methods (25).

GW1929, BADGE (Bisphenol A diglycidyl ether), SR202 and GW6471 were

purchased from Sigma-Aldrich (St. Louis, MO).

Cell lines

The UM-UC-9 cell line was purchased from Sigma-Aldrich (St. Louis, MO).

All other cell lines were obtained from the Cancer Cell Line Encyclopedia

(Broad Institute, Cambridge MA), which obtained them from the original source

and performed cell line authentication (26). To reduce bias from cell culture

medium, all cell lines were maintained in MEMalpha medium supplemented

with 10% Tet-system approved fetal bovine serum (FBS) (Clontech).

Ectopic cDNA expression:

Wild type ORFs for RXRA and PPARGv1 were obtained from the Genomics

Perturbation Platform (Broad Institute, Cambridge MA) in pDONR Gateway

cloning vectors. Various mutant alleles were generated using QuikChange Site-

Directed Mutagenesis (Agilent, Santa Clara CA). ORFs were then subcloned

RXRA and PPARG in Bladder Cancer

into lentiviral expression vectors using Gateway LR Clonase and infectious

lentiviral particles were generated using standard procedures.

SW780 bladder cancer cell line was transduced with a lentiviral vector

encoding the specified RXRA or PPARG ORF under control of constitutive

CMV or EF1α promoter, and stable pools were generated following selection for

blasticidin-resistance. Cell lines were maintained for at least 7 days following

selection prior to expansion for further analysis.

RNA sequencing analysis:

RNA was isolated using RNEasy (Qiagen, Germantown, MD) and an RNA

sequencing library was prepared using NEBNext Ultra Directional RNA Library

Prep Kit for Illumina and NEBNext Multiplex Oligos for Illumina (New England

BioLabs). Sample analysis was performed using a MiSeq System and reagent

kits (Illumina, San Diego, CA) according to the manufacturers protocol.

Sequence data was analyzed using Firehose (Broad Institute, Cambridge MA)

to map transcripts and calculate RPKM (SW780 cDNA expression) or TPM

(UM-UC-9).

For UM-UC-9 RNA sequencing experiment, the resulting reads were used

to calculate transcript abundance in units of TPM (transcripts per million) (27) ,

which were then adjusted using TMM normalization (28) for comparison. Log

fold-change and Mann-Whitney test significance was used to identify

differentially expressed genes between the agonist and inverse-agonist-treated

RXRA and PPARG in Bladder Cancer

samples.

Western blot analysis:

Cells were grown in 6-well plates and harvested using Complete Lysis-M

with protease and phosphatase inhibitors (Roche Applied Science, Germany).

Western blots were performed using standard protocols with semi-dry transfer

Trans-Blot® SD (Bio-Rad Hercules, CA), Li-Cor Odyssey Blocking buffer, and

imaging with LiCor Odyssey Imaging System (LI-COR Lincoln, NE). The anti-

PPARG C26H12, anti-PPARG 81B8, anti-FABP4 D25B3, and anti-CEACAM5

CB30 antibodies were obtained from Cell Signaling Technology (Beverly, MA).

The anti-ACSL5 ab57210 and anti-HMCGS2 EPR8642 antibodies were

obtained from Abcam (Cambridge, MA). The anti-VCL (vinculin) V9264

antibody was obtained from Sigma-Aldrich (St. Louis MO). All primary

antibodies were tested at 1:1000 dilutions, with the exception of anti-VCL,

which was tested at a 1:5000 dilution. Secondary goat anti-mouse 926-68020,

and goat-anti-rabbit 926-32211 antibodies were obtained from Li-Cor

Biosciences (Lincoln, NE) and used at 1:15,000 dilutions.

RT112-FABP4-NLucP reporter gene assay:

Reporter cell line was generated by engineering the NanoLuc gene into the

3’ UTR of FABP4 in RT112/84 cells using CRISPR/Cas9 guided genome

RXRA and PPARG in Bladder Cancer

engineering. Single cell clones were isolated and the clone with the widest

dynamic range selected for use. Assays were performed by seeding 384-well

plates with 10,000 cells per well in MEMalpha containing 10% FBS and dosing

compounds at indicated concentration using the HP D300 digital dispenser

(HP/Tecan). 18-24 hours after dosing with compound, cells were assayed using

NanoGlo Luciferase Assay Reagent (Promega Madison, WI) and plates were

read using an EnVision Multilabel Reader (PerkinElmer Waltham, MA).

Biochemical assays:

The LanthaScreen TR-FRET PPAR gamma Competitive Binding Assay and

LanthaScreen TR-FRET PPAR gamma Coactivator Assay were obtained from

ThermoFisher Scientific (Waltham, MA). Assays were performed according to

the manufacturer’s protocol. In order to assay inverse-agonism, the TR-FRET

PPAR gamma Coactivator assay was modified by the use of fluorescently

labeled corepressor peptides (NCoR1 ID2 peptide, SMRT ID2 peptide) in place

of TRAP220 coactivator peptide to convert from agonist mode (coactivator

recruitment) into inverse-agonist mode (corepressor recruitment).

Proliferation assays:

To enable cell-counting experiments, cell lines were transduced with a

lentiviral vector encoding nuclear-targeted GFP, TagGFP2-H2B (Evrogen,

Moscow, Russia), and stable pools generated following selection for

RXRA and PPARG in Bladder Cancer

puromycin-resistance. Cell lines were maintained for at least 7 days following

selection prior to expansion and seeding into 96-well or 384-well plates for

further analysis. For kinetic proliferation assays, 96-well plates (n = 4 per

condition) were imaged and counted every two hours using IncuCyte Zoom

(Essen BioScience, Ann Arbor MI). Media and compounds were replaced

approximately every 3-4 days. For end-point assays to measure dose-

response, cells were plated in 384-well plates, dosed with compound, and upon

reaching approximately 70-90% confluence in control wells, cells were either

counted using fluorescence imaging (IncuCyte Zoom) or incubated with

CyQuant (ThermoFisher, Waltham, MA) at the indicated time and plates were

read with a fluorescent plate reader.

CRISPR/Cas9 genetic dependency studies:

Cell lines were first transduced with a lentiviral vector encoding hSpCas9

under control of a tetracycline-inducible CMV promoter (CMV-TO,

ThermoFisher Scientific) and stable pools generated following selection for

blasticidin-resistance. Following confirmation of regulated Cas9 expression by

Western blot analysis, the cells were transduced with a lentiviral vector

encoding an sgRNA under control of a tetracycline-inducible H1 promoter (H1-

TO, ThermoFisher Scientific) and double-stable pools were generated following

selection for puromycin-resistance. In addition to providing for regulated sgRNA

expression, these lentiviral vectors also constitutively express one of three

RXRA and PPARG in Bladder Cancer

nuclear-targeted fluorescent proteins to enable unambiguous identification of

transduced cells in subsequent cell counting experiments: YFP-expressing

vectors were used for sgRNAs targeting PPARG; CFP-expressing vectors were

used for sgRNAs targeting non-essential control genes, and RFP-expressing

vectors were used for sgRNAs targeting essential control genes. This approach

is described in more detail elsewhere (Strathdee et al., manuscript in

preparation).

We evaluated 6-8 different sgRNAs per gene of interest using Western blot

analysis in order to identify 2-3 highly active, doxycyline-inducible guides

targeting PPARG (sgPPARG-3: GTCTTCTCAGAATAATAAGG, sgPPARG-6:

GTTTCAGAAATGCCTTGCAG) for use in our experiments. We used KIF11

(sgKIF11-3: GGTGGTGGTGAGATGCAGGT) as an essential control gene, and

an sgRNA targeting PPARG intronic sequence (sgPPARG-

21: GATACTGCTGCATTAGACCAG) was used as a non-essential controls.

Following generation of stable pools of for each sgRNA were combined in

equivalent numbers within replicate wells of 6-well plate and doxycycline was

added to one of the replicates to induce Cas9 and sgRNA. Cells were

passaged every 3-5 days and one replicate maintained under doxycycline

induction, with second replicate maintained in the absence of doxycycline.

During each passage, four replicate wells were passaged into 96-well plates for

fluorescent imaging and fixed with methanol for imaging 1-3 days after passage

into 96-well plates. Changes in relative abundance of cells containing the on-

RXRA and PPARG in Bladder Cancer

test sgRNA, non-essential sgRNA, and essential sgRNA were thus followed by

comparing relative abundance of cells based on fluorescent label (Yellow,

Cyan, Red) through serial passages for a period of 28 days. Cells with stably

transduced TREx inducible vectors were all maintained continuously in

MEMalpha medium containing 10% Tet-system approved FBS (Clontech).

Data availability:

Bladder cancer incidence and survival data was obtained from Howlader N,

Noone AM, Krapcho M, Miller D, Bishop K, Altekruse SF, et al. November 2015

SEER data submission, posted to the SEER web site, April 2016. SEER

Cancer Statistics Review, 1975-2013. National Cancer Institute

The provisional TCGA muscle-invasive urothelial carcinoma data is

available from the Broad Institute TCGA Genome Data Analysis Center.

Analysis-ready standardized TCGA data from Broad GDAC Firehose

2016_01_28 run. https://doi.org/10.7908/C11G0KM9. CCLE Affymetrix U133+2

arrays mRNA expression data is available through

https://portals.broadinstitute.org/ccle/ (26). RNA sequencing data is available

through the National Center for Biotechnology Information BioProject accession

# PRJNA396067.

RXRA and PPARG in Bladder Cancer

Results

PPARG signaling is activated by ectopic expression of RXRA p.S427F/Y

and PPARG p.T447M mutant alleles

To assess the biological effects of mutations in RXRA and PPARG, we

ectopically expressed cDNAs encoding wild-type and mutant alleles of each

gene in the SW780 bladder cancer cell line, which is wild-type for RXRA and

PPARG (26). RXRA hotspot mutant alleles p.S427F and p.S427Y, as well as a

PPARG mutant allele found in RT4 cells, p.T447M in PPARG isoform 1,

NP_005028, also commonly referred to as PPARG p.T475M in isoform 2,

NP_056953.2, were selected for initial testing. We performed RNA sequencing

on parental SW780 cells in comparison with cells expressing wild-type or

mutant PPARG or RXRA alleles. SW780 cells with ectopic expression of RXRA

p.S427F/Y and PPARG p.T447M mutant alleles demonstrated up-regulation of

canonical PPARA and PPARG target genes such as ACSL5, HMGCS2, and

FABP4 (Fig. 1A). Immunoblot assays confirmed significant up-regulation of

several of the corresponding proteins in SW780 cells expressing mutant RXRA

and PPARG alleles (Fig. 1B) even though parental SW780 cells appear to have

elevated expression of PPARG and PPARG target genes when compared to

other bladder cancer cell lines (Fig. 1C). These data are consistent with the

observations of increased expression of these PPAR targets in patient bladder

tumors bearing RXRA hotspot mutations (9).

We also noted a discrete set of genes up-regulated by RXRA p.S427F/Y,

RXRA and PPARG in Bladder Cancer

such as HMGSC2 and CEACAM5, which were minimally regulated by any of

the PPARG alleles. In follow-up immunoblot studies, we included wild-type

PPARA and observed that both HMGCS2 and CEACAM5 were selectively

upregulated upon ectopic expression of PPARA, but not PPARG (Fig. 1B),

indicating that these are likely PPARA targets. We also observed more

pronounced effects of RXRA p.S427F compared to the p.S427Y allele on gene

expression of HMGCS2, FABP4, and others by RNA sequencing (Fig. 1A),

confirmed on the protein level by immunoblot assays (Fig. 1B). This may

indicate a stronger phenotype for RXRA p.S427F, which is consistent with the

higher frequency of this allele in bladder cancer patients (9). Ectopic expression

of other RXRA mutant alleles, selected based on apparent clusters (eg.

p.P231L, p.E233K), and sequence proximity to S427 (p.R421C, p.R421H,

p.R426H, p.G429Y) from pan-cancer genomics analysis (29), had no activity in

these assays (Supplementary Fig. 2).

PPARG inverse-agonists decrease target gene expression in PPARG-

activated cell lines

The study of the phenotype of PPARG-activating genome alterations is

facilitated by a wide variety of compounds that modulate PPARG activity,

including agonists, antagonists, and inverse agonists. PPARG agonists

increase recruitment of coactivators such as CREBBP, PGC1 (PPARGC1A),

and MED1 to the RXRA-PPARG complex, leading to increased expression of

RXRA and PPARG in Bladder Cancer

target genes (Supplementary Fig. 3 - top) (30). PPARG inverse-agonists

recruit co-repressors such as NCOR1, NCOR2, and HDAC3, leading to a

decrease in basal expression of target genes (Supplementary Fig. 3 – bottom)

(30). In contrast, PPARG antagonists have minimal effects on basal receptor

function but are able to prevent both agonists and inverse-agonists from

binding the receptor, thereby blocking their effects (Supplementary Fig. 3) (30).

To evaluate the pharmacological inhibition of PPARG in bladder cancer cell

lines, we tested the impact of known PPARG modulating compounds in gene

expression assays. In preliminary experiments across a panel of PPARG-

activated bladder cancer cell lines (Fig. 1C) we found that dosing bladder

cancer cell lines with T0070907, a PPARG inverse-agonist (31), but not

GW9662, a PPARG antagonist (32), was able to reduce expression of the

canonical PPARG target gene, FABP4 (Supplementary Fig. 4). Although these

compounds have similar potency and selectivity profiles and share a

remarkably similar chemical structure (Supplementary Table 1), they behaved

quite differently in cells.

We engineered an FABP4 reporter cell line to enable higher throughput

assays with which to evaluate PPARG transactivation. Briefly, the NanoLuc

luciferase reporter gene was inserted into the 3’-UTR of the FABP4 gene in the

PPARG-activated RT112/84 bladder cancer cell line using CRISPR/Cas9

mediated homology-directed repair (Supplementary Fig. 5). Since many

compounds that target nuclear receptors are selective modulators which have

RXRA and PPARG in Bladder Cancer

context-dependent activity profiles (30), we used this reporter cell line to

characterize the activity of 13 previously characterized PPARG agonists,

antagonists, and inverse-agonists (18,25,31-40). The full PPARG agonists,

including rosiglitazone, pioglitazone, tesaglitazar, and GW1929, were able to

increase the basal activity of the PPARG reporter from 5.5 to 7.4 fold in this

assay (Figure 2A, indicated in red). The partial agonists, including UVI3003

and SR1664, increased the basal activity of the reporter from 1.4 to 3.1 fold

(Fig. 2A, indicated in black). The antagonists, including BADGE, SR202,

GW9662, and SR2595, had minimal detectable effect on this unstimulated

reporter (Fig. 2A, indicated in light blue). The PPARA-selective inverse agonist

GW6471 exerted a modest inhibitory effect. Finally, the two inverse-agonists

tested, T0070907 and SR10221, reduced basal PPARG reporter activity by 85

to 88 percent (Fig. 2A, indicated in dark blue and green). Interestingly, the

closely related structural analogs (Supplementary Table 1) of these

compounds, GW9662 and SR2595, respectively, were essentially neutral

antagonists in this assay.

To evaluate antagonist and inverse-agonist activity in more detail,

compounds were tested in the presence of a PPARG agonist, rosiglitazone, for

their impact on ligand-activated PPARG reporter activity. Here, the agonists

gave little additional stimulation (Fig. 2B, indicated in black). The antagonists

GW9662 and SR2595 decreased the agonist-induced signal back to the

original baseline (Fig. 2B, indicated in light blue), whereas the inverse-agonists

RXRA and PPARG in Bladder Cancer

T0070907 and SR10221 further reduced the agonist-induced signal 80-90%

below baseline (Fig. 2B, indicated in dark blue and green). These data align

with quantitative PCR analysis of FABP4 gene expression in 5637 and UM-UC-

9 cells treated with PPARG antagonists and inverse-agonists (Supplementary

Fig. 6) and establish that the reporter assay accurately represents the effects of

PPARG modulators on target gene expression in bladder cancer cell lines.

We next evaluated the effects of long-term dosing on the transcriptional

profile of the PPARG-amplified cell line, UM-UC-9. Briefly, UM-UC-9 cells were

treated for 7 days with various PPARG modulators dosed at 500 nM and gene

expression was analyzed using RNA sequencing. Many canonical PPARG

target genes were amongst the top differentially expressed genes that were

upregulated with PPARG agonists and downregulated with inverse-agonists, for

example FABP4 and UCP1 (Supplementary Fig. 7). Genes that were more

abundantly expressed upon treatment with inverse-agonists included ALPP,

SPINK4, and ALDH1A3 (Supplementary Fig. 7). Hierarchical clustering of the

gene expression signatures indicated that GW9662 and SR2595 cluster with

vehicle-treated controls. Therefore, the PPARG inverse-agonists, T0070907

and SR10221, are clearly biologically distinct from the antagonists, GW9662

and SR2595, in bladder cancer cells. While both SR2595 and SR10221 were

described as PPARG inverse-agonists when tested in mouse 3T3-L1 cells (25),

our studies using human bladder cancer cells suggest that SR10221, but not

SR2595, behaves as an inverse-agonist in these cells (Fig. 2 and

RXRA and PPARG in Bladder Cancer

Supplementary Figs. 6-7). In summary, we have characterized the in vitro

pharmacological properties of known PPARG modulators and have identified

two distinct chemotypes with bona-fide inverse-agonist activity in PPARG-

activated bladder cancer cells.

PPARG inverse-agonists induce a repressive complex through inducing

interactions with co-repressor NCOR2

To determine effects on interactions between PPARG and co-regulators, we

tested PPARG modulators in two TR-FRET biochemical interaction assays for

agonism and inverse-agonism. Agonism was quantitated using a co-activator

assay, which measured the interaction between the PPARG ligand-binding

domain and a fluorescently-labeled peptide from TRAP220/MED1. Full

agonists, such as rosiglitazone, tesaglitazar, GW1929, and pioglitazone,

enhanced interaction between PPARG and MED1 coactivator peptide, resulting

in an increase in fluorescent signal from 2.2 to 3.0 fold (Fig. 3A, indicated in

red). The antagonists and partial agonists, BADGE, SR202, GW9662,

UVI3003, and SR1664 had minimal effect in this assay (Fig. 3A, indicated in

gray and light blue). The PPARA-selective inverse-agonist GW6471, PPARG

antagonist SR2595, and PPARG inverse-agonists, T0070907, and SR10221,

exerted a modest inhibitory effect of 40-60%. (Fig. 3A, indicated in dark blue

and gray).

To evaluate inverse-agonism biochemically, we measured ligand-dependent

RXRA and PPARG in Bladder Cancer

interactions between PPARG ligand-binding domain and corepressor peptides

from NCoR/NCOR1 and SMRT/NCOR2. The majority of PPARG partial-

agonists and antagonists had minimal effect on the NCOR2 assay signal (Fig.

3B). PPARG inverse-agonists, T0070907 and SR10221 (Fig. 3B, indicated in

dark blue), increased signal 3-6 fold, while antagonists GW9662 and SR2595

(Fig. 3B, indicated in light blue), induced only a small increase in signal of 1.7-

fold. A decrease in signal of 50-60% was observed with the rosiglitazone,

tesaglitazar, and GW9129 agonists (Fig. 3B, indicated in red).

In addition to the PPARG-NCOR2 interaction assay described above, we

measured interactions between PPARG and a peptide from the corepressor

NCOR1. In the PPARG-NCOR1 interaction assay, T0070907 induced signal 6-

8-fold, while the antagonist GW9662 induced signal 2.5-fold and inverse

agonist, SR10221, induced signal less than 2-fold, and antagonist, SR2595,

had no effect (data not shown). The potent inverse-agonist activity of SR10221

in cellular assays (Fig. 2 and Supplementary Figs. 6-7) and biochemical

PPARG-LBD - NCOR2 assay (Fig. 3B), but not PPARG-LBD - NCOR1

interaction assay (Fig. 3B), suggests that NCOR2 may be the functional co-

repressor mediating PPARG inverse-agonist activity in bladder cancer cells.

PPARG inverse-agonists inhibit the proliferation of PPARG-activated cell

lines

To determine whether PPARG modulators affect the proliferation and/or

RXRA and PPARG in Bladder Cancer

viability of PPARG-activated bladder cancer cell lines, we performed a direct

cell counting-based assay. This assay likely avoids potential artifacts

associated with the use of an ATP content-based assay, given that PPAR

modulators are known to regulate cellular metabolic activity.

Both inverse-agonists, T0070907 and SR10221, significantly reduced

proliferation of UM-UC-9 cells, compared to DMSO control (P<0.001) (Fig. 4A,

indicated in green), with calculated IC50 values of 39 nM and 16 nM. In

contrast, both antagonists tested, GW9662 and SR2595, had no significant

effects on cell proliferation (Fig. 4A, indicated in gray). These IC50 values align

well with the calculated IC50s from both the cell-based reporter gene assay

(Fig. 2A) and the biochemical co-repressor assay (Fig. 3B). They are also close

to the respective reported biochemical IC50s against PPARG, and two orders

of magnitude below that reported for activity against PPARA and PPARD (31),

suggesting that the observed anti-proliferative effects in UM-UC-9 cells are due

to downregulation of PPARG target genes.

We expanded this assay to include an additional 8 representative bladder

cancer cell lines, including cell lines with PPARG amplification, RXRA p.S427F

mutation, activated gene signature, and control cell lines with low level

expression of PPARG and target genes. As we could not always accurately

calculate an IC50 value, we used an alternative quantitative endpoint assay,

which measures the relative number of cells in the DMSO vehicle control

compared to treatment with 100 nM of each compound with analysis performed

RXRA and PPARG in Bladder Cancer

at the time required for the cells to reach 50% confluency in the DMSO control.

Representative data for the UM-UC-9 cell line are shown in Figure 4B, and is

tabulated for the tested bladder cancer cell lines in Table 1. Similar to the full

dose-response assay (Fig. 4A), the T0070907 and SR10221 inverse-agonists

reduce proliferation by 81% and 80% relative to control, whereas the GW9662

and SR2595 antagonists have no effect. This significant (P<0.01) preferential

sensitivity to PPARG inverse-agonists, but not antagonists, is maintained

across all of the PPARG-activated cell lines in the panel, including the RXRA

p.S427F cell line, HT-1197 (41), the PPARG-amplified cell lines, 5637 and UM-

UC-9, and the PPARG-activation gene signature cell lines Cal29, UM-UC-1,

and RT112/84 (Table 1). The SW1710, UM-UC-3, and KU19.19 cells lines that

did not exhibit high expression of PPARG or target genes (Fig. 1C) were

insensitive to PPARG inverse-agonists and antagonists (Table 1). We obtained

similar results with these cell lines in parallel studies using clonogenic assays to

quantify colony forming ability (Supplementary Figure 8). These data reveal that

proliferation of the PPARG-activated subset of bladder cancer cell lines, but not

control bladder cancer cell lines, is dependent on PPARG activity, and inhibition

of this activity with the inverse-agonists, T0070907 or SR10221, results in

decreased proliferative potential.

PPARG-activated cell lines are genetically dependent on PPARG

To test for PPARG dependency in PPARG-activated cell lines with an

RXRA and PPARG in Bladder Cancer

orthogonal approach, we performed CRISPR/Cas9 knockout studies using a

high-precision multicolor competition dependency assay (Strathdee et al.,

manuscript in preparation). Briefly, we first validated that guide RNAs against

PPARG were able to significantly diminish PPARG expression by Western

immunoblot after normalization to loading control vinculin, VCL (Fig. 5A, B). We

next compared the relative effect of knockout of PPARG on cell proliferation to

knockout of an essential gene (KIF11) and to knockout of a non-essential gene

(HPRT or PPIB) or PPARG intron control. The sgRNAs targeting these genes

were cloned into lentiviral vectors that co-express one of three different

fluorescent proteins, YFP, RFP, or CFP, and which allowed for unambiguous

identification of transduced cells in complex pools: PPARG knockout cells were

labeled with YFP, essential control knockout cells were labeled with RFP, and

non-essential (or PPARG intron) control knockout cells were labeled with CFP.

In the competition format, replicate pools of cells are generated at the

beginning of the experiment in which each gene knockout/color are at

equivalent abundance. Changes in relative abundance of each population are

monitored during progressive serial passage by counting fluorescent nuclei

using high-content imaging. Relative changes are plotted as Percent of Control

(POC) of the normalized prevalence of on-test sgRNAs as a percent of non-

essential sgRNA control targeting an intron of PPARG.

Analysis of three bladder cancer cell lines showed a clear PPARG

dependency in PPARG-activated cells. The growth of the SW1710 cell line,

RXRA and PPARG in Bladder Cancer

which shows low PPARG/FABP4 expression (Fig. 1C), is insensitive to PPARG

knockout (Fig. 5C). In contrast, HT-1197 the only known cell line with an RXRA

p.S427F mutation (41), exhibited a strong PPARG-dependency in this CRISPR

competition assay (Fig. 5D). The Cal29 cell line, with a highly activated PPARG

signaling pathway (Fig. 1), also exhibits clear PPARG dependency (Fig. 5E). In

preliminary experiments we determined that the RT4 cell line supported

inadequate hCas9 expression for use in gene knockout experiments, which is

unfortunate since it is the only cell line available with a PPARG p.T447M

mutation. Note that we did not include any cell lines containing PPARG focal

amplifications in order to avoid the well-known copy number sensitivity artifact

inherent to the CRISPR/Cas9 platform (42,43). We conclude that from the

above analyses that PPARG-activated bladder cancer cell lines are dependent

upon a functional PPARG.

Discussion

Recently, genomic analysis of bladder cancer revealed that the PPARG

signaling pathway is significantly activated in tumors, and that this can be

driven by either RXRA p.S427F/Y mutations or PPARG focal amplifications

(9,15). Here we confirm that these alterations, in addition to PPARG p.T447M

mutation which may be emerging as a new hotspot (Supplementary Figure 10),

RXRA and PPARG in Bladder Cancer

activate the PPARG signaling pathway, and that cell lines with the

corresponding mutations are genetically-dependent on PPARG and are also

sensitive to pharmacological inactivation using PPARG inverse-agonists.

One model to explain this data is that these alterations confer ligand-

independent activation of PPARG. In the case of RXRA p.S427F/Y and PPARG

p.T447M mutations this could be achieved by the gain of hydrophobic

interactions that lock PPARG helix 12 into the active conformation,

phenocopying the agonist-induced state in the absence of ligand. Co-crystal

structures of RXRA/PPARG (e.g. PDB ID: 1FM6 and PDB ID: 5JI0) (15,44)

show that the S427 position of RXRA is located in the dimerization interface

with PPARG in the ligand-activated state, directly adjacent to both the T447

residue and c-terminus Y477 residue of PPARG. This positioning is also

conserved in homology models of RXRA/PPARA (45). RXRA p.S427F/Y

mutations may also disrupt interactions between RXRA and its other

heterodimer partners (eg. RARA, VDR, TR), further shifting equilibrium of

RXRA further towards PPARs (15).

It has been established that other mechanisms can lead to ligand-

independent activation of PPARG. For example, signaling by insulin through

the actions of MAP kinases leads to phosphorylation of PPARG in the AF-1

domain which can lead to ligand-independent activation (46). Insulin-dependent

PPARG activation is not sensitive to inhibition by the PPARG antagonist

GW9662, whereas ligand-driven activation by PPARG agonist, cigitazone, is

RXRA and PPARG in Bladder Cancer

sensitive to GW9662 (47). Here we show that PPARG-activated bladder cancer

cells, through PPARG amplification, RXRA p.S427F mutation, or other

unknown mechanisms, are similarly not responsive to antagonists, including

GW9662 and SR2595, but are sensitive to inverse-agonists. Since PPARG

inverse-agonists induce a conformational change in the ligand-binding domain

to actively recruit co-repressors to the complex, these could overcome ligand-

independent signaling, as our studies show.

The impact of PPARG on bladder cancer signaling is supported by the

evidence that PPARA/PPARG dual agonists cause bladder cancer in rodents,

although there are conflicting epidemiological data that PPARA/PPARG

agonists are associated with increased rates of disease in humans (20,22-

24,48).

PPARG as a therapeutic target in bladder cancer can be seen as analogous

to targeting androgen receptor in prostate cancer or estrogen receptor in breast

cancer. One of the hallmarks of luminal cancers is the expression of a ligand-

activated nuclear receptor. Therapeutic targeting of the nuclear receptors in

patients with these cancers can be a very effective therapeutic approach as in

the example of targeting ESR1-positive luminal breast cancer with anti-

estrogens and AR-positive prostate cancer with androgen deprivation therapy.

PPARG agonists upregulate expression of luminal differentiation markers

UPK1A, UPK1B, and KRT20 in primary rat urothelial cells (49). These same

genes, plus GATA3, and FOXA1 are the key luminal markers of bladder cancer

RXRA and PPARG in Bladder Cancer

from human patients (13,14) and bladder cancer cell lines (16). The lineage-

defining role of GATA3, FOXA1, and PPARG in luminal bladder cancer is

reminiscent of luminal breast cancer, in which coordinated expression of

GATA3, FOXA1, and ESR1 enable chromatin remodeling and regulate luminal

gene expression programs (50,51). Whereas in prostate cancer, FOXA1 and

GATA2 (52) coordinately regulate the activity AR (53) and distribution and

selectivity for AR response elements.

The steroid hormone receptors ESR1 and AR are also in the nuclear

receptor superfamily, however, distinct from PPARG, they utilize high affinity

ligands for signaling. Endogenous production of estrogen in breast tissue, and

testosterone / dihyrotestosterone in the testes, are required for receptor

activation. Therefore, in the context of ligand-activation, antagonists of ESR1

and AR are effective therapies for primary cancers. Another effective strategy in

breast and prostate cancer are therapies leading to inhibition of ligand

production such as the use of aromatase inhibitors for treatment of breast

cancer and androgen deprivation therapy for prostate cancer. In contrast,

PPARG does not have a high-affinity endogenous ligand and is considered a

lipid sensor, with low affinity for its ligands (54). Therefore, mechanisms leading

to ligand-independent activation of PPARG, and not ligand-dependent

signaling, appear to be the primary driver of PPARG activity and will require a

different pharmacological properties than in the case of targeting ligand-

RXRA and PPARG in Bladder Cancer

activated ESR1 or AR with a pure antagonist.

Patients treated with anti-estrogen and anti-androgen therapy commonly

develop resistance, with common mechanisms being somatic alterations that

lead to either ligand hypersensitivity or ligand-independent signaling. In the

case of ESR1, recurrent mutations at Y537 mutations lead to ligand-

independent signaling (Robinson et al 2013) and due to being in the ligand-

binding domain, also confer resistance to ESR1 antagonists. In the case of AR,

gene amplification leads to ligand hypersensitivity, whereas point mutations and

alternative splicing can lead to ligand-independent activation (55). In order to

attenuate ligand-independent activation of ESR1, a new class of compounds

was developed that lead to receptor degradation. Selective estrogen receptor

degraders have had promising clinical outcomes, with fulvestrant reaching

clinical approval and providing a new hope for ER+ breast cancer patients

refractory to SERMs and aromatase inhibitors. Based on the fact that there

appears to be high level of ligand-independent PPARG signaling in bladder

cancer, we focused efforts on validating inverse-agonists as a candidate

therapeutic strategy. However, a selective PPARG-destabilizer could be

another promising therapeutic approach worth exploring.

We have demonstrated a genetic and pharmacologic dependence on

PPARG in PPARG-activated, luminal bladder cancer cell lines. Our studies

RXRA and PPARG in Bladder Cancer

provide a well-defined patient population and clear therapeutic hypothesis.

Since PPARG agonists rosiglitazone and pioglitazone are used for the

treatment of diabetes by a mechanism of sensitizing cells to insulin, lowering

blood glucose, and lowering lipid levels (56), one may predict that a PPARG

inverse-agonist may have an opposing effect, eliciting symptoms of diabetes.

Furthermore, patients with deleterious PPARG mutations have an increased

risk for diabetes and can exhibit lipodystrophy and insulin resistance (57). While

there are concerns for on-mechanism complications for PPARG inverse-

agonists as a potential therapy for bladder cancer, there is renewed hope that

rigorous testing and a deep understanding of emerging PPARG biology and

pharmacology (25) can overcome these hurdles through selective receptor

modulation. Recent advances have highlighted a potential role for oncogenic

activation of PPARG in bladder cancer to regulate inflammatory cytokines,

thereby regulating immune cell infiltration and immunosurveillance (15). Further

studies of PPARG in bladder cancer will help to evaluate whether PPARG

inverse agonists can complement conventional and emerging therapies

including other genomically defined therapeutic targets such as FGFR

inhibitors, in addition to immune checkpoint blockade.

RXRA and PPARG in Bladder Cancer

Acknowledgements

The authors would like to thank Xiaoyang Zhang, Josh Francis, Chandra

Pedamallu, Patrick McCarren, Chris Lemke, Aruna Ramachandran Robert

Hilgraf, Stuart Schreiber, and Todd Golub for their helpful discussions and

guidance.

RXRA and PPARG in Bladder Cancer

References

1. Rosenberg JE, Hoffman‐Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A, et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum‐based chemotherapy: a single‐arm, multicentre, phase 2 trial. The Lancet 2016;387:1909‐20 2. Sharma P, Retz M, Siefker‐Radtke A, Baron A, Necchi A, Bedke J, et al. Nivolumab in metastatic urothelial carcinoma after platinum therapy (CheckMate 275): a multicentre, single‐arm, phase 2 trial. Lancet Oncol 2017;18:312‐22 3. Apolo AB, Infante JR, Balmanoukian A, Patel MR, Wang D, Kelly K, et al. Avelumab, an Anti‐Programmed Death‐Ligand 1 Antibody, In Patients With Refractory Metastatic Urothelial Carcinoma: Results From a Multicenter, Phase Ib Study. J Clin Oncol 2017;35:2117‐24 4. Massard C, Gordon MS, Sharma S, Rafii S, Wainberg ZA, Luke J, et al. Safety and Efficacy of Durvalumab (MEDI4736), an Anti‐Programmed Cell Death Ligand‐1 Immune Checkpoint Inhibitor, in Patients With Advanced Urothelial Bladder Cancer. J Clin Oncol 2016;34:3119‐25 5. Iyer G, Hanrahan AJ, Milowsky MI, Al‐Ahmadie H, Scott SN, Janakiraman M, et al. Genome sequencing identifies a basis for everolimus sensitivity. Science 2012;338:221 6. Liu D, Plimack ER, Hoffman‐Censits J, Garraway LA, Bellmunt J, Van Allen E, et al. Clinical Validation of Chemotherapy Response Biomarker ERCC2 in Muscle‐Invasive Urothelial Bladder Carcinoma. JAMA Oncology 2016;2:1094 7. Van Allen EM, Mouw KW, Kim P, Iyer G, Wagle N, Al‐Ahmadie H, et al. Somatic ERCC2 mutations correlate with cisplatin sensitivity in muscle‐invasive urothelial carcinoma. Cancer Discov 2014;4:1140‐53 8. Wagle N, Grabiner BC, Van Allen EM, Hodis E, Jacobus S, Supko JG, et al. Activating mTOR mutations in a patient with an extraordinary response on a phase I trial of everolimus and pazopanib. Cancer Discov 2014;4:546‐53 9. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 2014;507:315‐22 10. Guo G, Sun X, Chen C, Wu S, Huang P, Li Z, et al. Whole‐genome and whole‐ exome sequencing of bladder cancer identifies frequent alterations in genes involved in sister chromatid cohesion and segregation. Nat Genet 2013;45:1459‐63 11. Evans Ronald M, Mangelsdorf David J. Nuclear Receptors, RXR, and the Big Bang. Cell 2014;157:255‐66 12. Ahmadian M, Suh JM, Hah N, Liddle C, Atkins AR, Downes M, et al. PPARgamma signaling and metabolism: the good, the bad and the future. Nat 31

RXRA and PPARG in Bladder Cancer

Med 2013;19:557‐66 13. Biton A, Bernard‐Pierrot I, Lou Y, Krucker C, Chapeaublanc E, Rubio‐Perez C, et al. Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes. Cell Rep 2014;9:1235‐45 14. Choi W, Porten S, Kim S, Willis D, Plimack Elizabeth R, Hoffman‐Censits J, et al. Identification of Distinct Basal and Luminal Subtypes of Muscle‐Invasive Bladder Cancer with Different Sensitivities to Frontline Chemotherapy. Cancer Cell 2014;25:152‐65 15. Korpal M, Puyang X, Jeremy Wu Z, Seiler R, Furman C, Oo HZ, et al. Evasion of immunosurveillance by genomic alterations of PPARγ/RXRα in bladder cancer. Nature Communications 2017;8 16. Warrick JI, Walter V, Yamashita H, Chung E, Shuman L, Amponsa VO, et al. FOXA1, GATA3 and PPAR Cooperate to Drive Luminal Subtype in Bladder Cancer: A Molecular Analysis of Established Human Cell Lines. Sci Rep 2016;6:38531 17. El Hage J. Toxicity Profiles of Peroxisome Proliferator‐Activated Receptor (PPAR) Agonists and Preclinical Safety Profile for Muraglitazar. FDA Report CDER 2005 18. Sakamoto J, Kimura H, Moriyama S, Odaka H, Momose Y, Sugiyama Y, et al. Activation of human peroxisome proliferator‐activated receptor (PPAR) subtypes by pioglitazone. Biochem Biophys Res Commun 2000;278:704‐11 19. Tannehill‐Gregg SH, Sanderson TP, Minnema D, Voelker R, Ulland B, Cohen SM, et al. Rodent carcinogenicity profile of the antidiabetic dual PPAR alpha and gamma agonist muraglitazar. Toxicol Sci 2007;98:258‐70 20. Lubet RA, Fischer SM, Steele VE, Juliana MM, Desmond R, Grubbs CJ. Rosiglitazone, a PPAR gamma agonist: potent promoter of hydroxybutyl(butyl)nitrosamine‐induced urinary bladder cancers. Int J Cancer 2008;123:2254‐9 21. Dominick MA, White MR, Sanderson TP, Van Vleet T, Cohen SM, Arnold LE, et al. Urothelial carcinogenesis in the urinary bladder of male rats treated with muraglitazar, a PPAR alpha/gamma agonist: Evidence for urolithiasis as the inciting event in the mode of action. Toxicol Pathol 2006;34:903‐20 22. Lewis JD, Habel LA, Quesenberry CP, Strom BL, Peng T, Hedderson MM, et al. Pioglitazone Use and Risk of Bladder Cancer and Other Common Cancers in Persons With Diabetes. Jama 2015;314:265 23. Tseng CH. Pioglitazone and bladder cancer in human studies: is it diabetes itself, diabetes drugs, flawed analyses or different ethnicities? J Formos Med Assoc 2012;111:123‐31 24. Tuccori M, Filion KB, Yin H, Yu OH, Platt RW, Azoulay L. Pioglitazone use and risk of bladder cancer: population based cohort study. BMJ 2016:i1541 25. Marciano DP, Kuruvilla DS, Boregowda SV, Asteian A, Hughes TS, Garcia‐ Ordonez R, et al. Pharmacological repression of PPARgamma promotes osteogenesis. Nat Commun 2015;6:7443 32

RXRA and PPARG in Bladder Cancer

26. Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 2012;483:603‐7 27. Bray NL, Pimentel H, Melsted P, Pachter L. Near‐optimal probabilistic RNA‐ seq quantification. Nature Biotechnology 2016;34:525‐7 28. Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA‐seq data. Genome Biology 2010;11:R25 29. Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, Golub TR, et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 2014;505:495‐501 30. Gronemeyer H, Gustafsson JA, Laudet V. Principles for modulation of the nuclear receptor superfamily. Nat Rev Drug Discov 2004;3:950‐64 31. Lee G, Elwood F, McNally J, Weiszmann J, Lindstrom M, Amaral K, et al. T0070907, a selective ligand for peroxisome proliferator‐activated receptor gamma, functions as an antagonist of biochemical and cellular activities. J Biol Chem 2002;277:19649‐57 32. Leesnitzer LM, Parks DJ, Bledsoe RK, Cobb JE, Collins JL, Consler TG, et al. Functional consequences of cysteine modification in the ligand binding sites of peroxisome proliferator activated receptors by GW9662. Biochemistry 2002;41:6640‐50 33. Brown KK, Henke BR, Blanchard SG, Cobb JE, Mook R, Kaldor I, et al. A novel N‐aryl tyrosine activator of peroxisome proliferator‐activated receptor‐ gamma reverses the diabetic phenotype of the Zucker diabetic fatty rat. Diabetes 1999;48:1415‐24 34. Cesario RM, Klausing K, Razzaghi H, Crombie D, Rungta D, Heyman RA, et al. The rexinoid LG100754 is a novel RXR:PPARgamma agonist and decreases glucose levels in vivo. Mol Endocrinol 2001;15:1360‐9 35. Choi JH, Banks AS, Estall JL, Kajimura S, Boström P, Laznik D, et al. Anti‐ diabetic drugs inhibit obesity‐linked phosphorylation of PPARγ by Cdk5. Nature 2010;466:451‐6 36. Cronet P, Petersen JF, Folmer R, Blomberg N, Sjoblom K, Karlsson U, et al. Structure of the PPARalpha and ‐gamma ligand binding domain in complex with AZ 242; ligand selectivity and agonist activation in the PPAR family. Structure 2001;9:699‐706 37. Lehmann JM, Moore LB, Smith‐Oliver TA, Wilkison WO, Willson TM, Kliewer SA. An antidiabetic thiazolidinedione is a high affinity ligand for peroxisome proliferator‐activated receptor gamma (PPAR gamma). J Biol Chem 1995;270:12953‐6 38. Rieusset J, Touri F, Michalik L, Escher P, Desvergne B, Niesor E, et al. A new selective peroxisome proliferator‐activated receptor gamma antagonist with antiobesity and antidiabetic activity. Mol Endocrinol 2002;16:2628‐44 39. Wright HM, Clish CB, Mikami T, Hauser S, Yanagi K, Hiramatsu R, et al. A synthetic antagonist for the peroxisome proliferator‐activated receptor gamma inhibits adipocyte differentiation. J Biol Chem 2000;275:1873‐7 33

RXRA and PPARG in Bladder Cancer

40. Xu HE, Stanley TB, Montana VG, Lambert MH, Shearer BG, Cobb JE, et al. Structural basis for antagonist‐mediated recruitment of nuclear co‐ repressors by PPARalpha. Nature 2002;415:813‐7 41. Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: somatic cancer genetics at high‐resolution. Nucleic Acids Research 2017;45:D777‐D83 42. Aguirre AJ, Meyers RM, Weir BA, Vazquez F, Zhang CZ, Ben‐David U, et al. Genomic Copy Number Dictates a Gene‐Independent Cell Response to CRISPR/Cas9 Targeting. Cancer Discov 2016;6:914‐29 43. Munoz DM, Cassiani PJ, Li L, Billy E, Korn JM, Jones MD, et al. CRISPR Screens Provide a Comprehensive Assessment of Cancer Vulnerabilities but Generate False‐Positive Hits for Highly Amplified Genomic Regions. Cancer Discov 2016;6:900‐13 44. Gampe RT, Jr., Montana VG, Lambert MH, Miller AB, Bledsoe RK, Milburn MV, et al. Asymmetry in the PPARgamma/RXRalpha crystal structure reveals the molecular basis of heterodimerization among nuclear receptors. Mol Cell 2000;5:545‐55 45. Venalainen T, Molnar F, Oostenbrink C, Carlberg C, Perakyla M. Molecular mechanism of allosteric communication in the human PPARalpha‐RXRalpha heterodimer. Proteins 2010;78:873‐87 46. Zhang B, Berger J, Zhou G, Elbrecht A, Biswas S, White‐Carrington S, et al. Insulin‐ and Mitogen‐activated Protein Kinase‐mediated Phosphorylation and Activation of Peroxisome Proliferator‐activated Receptor Journal of Biological Chemistry 1996;271:31771‐4 47. Al‐Rasheed NM, Chana RS, Baines RJ, Willars GB, Brunskill NJ. Ligand‐ independent activation of peroxisome proliferator‐activated receptor‐ gamma by insulin and C‐peptide in kidney proximal tubular cells: dependent on phosphatidylinositol 3‐kinase activity. J Biol Chem 2004;279:49747‐54 48. Turner RM, Kwok CS, Chen‐Turner C, Maduakor CA, Singh S, Loke YK. Thiazolidinediones and associated risk of bladder cancer: a systematic review and meta‐analysis. Br J Clin Pharmacol 2014;78:258‐73 49. Varley CL, Southgate J. Effects of PPAR agonists on proliferation and differentiation in human urothelium. Exp Toxicol Pathol 2008;60:435‐41 50. Theodorou V, Stark R, Menon S, Carroll JS. GATA3 acts upstream of FOXA1 in mediating ESR1 binding by shaping enhancer accessibility. Genome Res 2013;23:12‐22 51. Eeckhoute J, Keeton EK, Lupien M, Krum SA, Carroll JS, Brown M. Positive cross‐regulatory loop ties GATA‐3 to estrogen receptor alpha expression in breast cancer. Cancer Res 2007;67:6477‐83 52. Zhao JC, Fong KW, Jin HJ, Yang YA, Kim J, Yu J. FOXA1 acts upstream of GATA2 and AR in hormonal regulation of gene expression. Oncogene 2016;35:4335‐ 44 53. Jin HJ, Zhao JC, Wu L, Kim J, Yu J. Cooperativity and equilibrium with FOXA1 define the androgen receptor transcriptional program. Nat Commun 34

RXRA and PPARG in Bladder Cancer

2014;5:3972 54. Poulsen L, Siersbaek M, Mandrup S. PPARs: fatty acid sensors controlling metabolism. Semin Cell Dev Biol 2012;23:631‐9 55. Chandrasekar T, Yang JC, Gao AC, Evans CP. Mechanisms of resistance in castration‐resistant prostate cancer (CRPC). Transl Androl Urol 2015;4:365‐80 56. Saltiel AR, Olefsky JM. Thiazolidinediones in the treatment of insulin resistance and type II diabetes. Diabetes 1996;45:1661‐9 57. Semple RK, Chatterjee VK, O'Rahilly S. PPAR gamma and human metabolic disease. J Clin Invest 2006;116:581‐9

RXRA and PPARG in Bladder Cancer

Table 1

Cell Line Pathway Alteration GW9662 SR2595 T0070907 SR10221

HT‐1197 RXRA p.S427F 127 78 48** 64*

5637 PPARG amplified 93 117 51** 73**

UM‐UC‐9 PPARG amplified 108 97 19** 20**

RT112/84 PPARG signature 98 101 69** 80**

UM‐UC‐1 PPARG signature 96 84 47** 62**

Cal29 PPARG signature 97 86 55** 74*

SW1710 Not altered 99 91 96 81

KU19.19 Not altered 85 91 95 91

UM‐UC‐3 Not altered 92 102 91 96 *, P <0.01 ** , P<0.001

Relative proliferation rate of bladder cancer cell lines treated with PPARG

inhibitors at 100nM compared to DMSO vehicle, reported as percent of vehicle

control (POC), in long-term kinetic proliferation assays. Percent of DMSO

control was calculated by determining the relative number of cells for treatment

versus DMSO control at the timepoint where DMSO control reached 50%

confluence (see Fig. 4B for graphical representation) by counting fluorescently

labeled nuclei (IncuCyte Zoom). Significant differences in cell number for test

sample relative to DMSO control were calculated using two-way ANOVA with

Dunnett’s multiple comparison test(*P<0.01, **P <0.001).

RXRA and PPARG in Bladder Cancer

Figure Legends

Figure 1. PPARG signaling is activated by ectopic expression of RXRA

p.S427F/Y and PPARG p.T447M mutant alleles. A, RNA expression (RSEM)

of selected genes that were differentially expressed when comparing parental

SW780 cells, cells with ectopic expression of wild-type RXRA and PPARG, and

cells expressing mutant alleles of RXRA and PPARG. B, Immunoblot analysis

of lysates from SW780 cells ectopically expressing RXRA and PPARG wild-

type and activating mutant alleles. C, Heatmap of Cancer Cell Line

Encyclopedia (CCLE) gene-centric RMA-normalized mRNA expression data

(26) across bladder cancer cell lines indicating luminal differentiation markers

and PPARG target genes. The samples were grouped by hierarchical clustering

of columns using the Morpheus software package

(https://software.broadinstitute.org/morpheus/).

Figure 2. PPARG inverse-agonists decrease basal activity by inducing

active repression. PPARG-activated RT112/84 bladder cancer cell line

engineered to contain the NanoLuc gene in the 3’ UTR of a canonical PPARG

target gene, FABP4, was used to profile the effect of compounds on PPARG-

dependent gene transactivation. A, Dose-response testing of panel of PPARG

modulators in the RT112/84 FABP4-NLucP reporter assay under unstimulated

conditions to evaluate activity of agonists and inverse-agonists. B, Antagonist

RXRA and PPARG in Bladder Cancer

mode dose-response testing of panel of PPARG modulators in the RT112/84

FABP4-NLucP reporter assay performed by combined dosing of the PPARG

agonist, rosiglitazone at the EC50, 20nM, in combination with a dose-response

for test compounds, as indicated.

Figure 3. PPARG inverse-agonists induce a repressive complex by

blocking interactions with coactivators and inducing interactions with co-

repressor NCOR2. A TR-FRET assay was used to evaluate the ligand-

dependent interactions between Terbium-labeled PPARG ligand binding

domain (PPARG-LBD) and fluorescein-labeled peptides derived from nuclear

receptor coregulators, as indicated. A, Dose-response testing of a panel of

PPARG modulators in an agonist biochemical model evaluating in a PPARG-

LBD - TRAP220 (MED1) co-activator peptide interaction assay to measure

agonist-induced interactions, or inverse-agonist induced decrease in

interactions. B, Dose-response testing of a panel of PPARG modulators in an

inverse-agonist biochemical model evaluating PPARG LBD – SMRT (NCOR2)

co-repressor interactions.

Figure 4. PPARG inverse-agonists, but not antagonists, inhibit

proliferation of PPARG-activated bladder cancer cell lines. A, proliferation

assay measuring dose-dependent effect of PPARG modulators on cell number

in UM-UC-9 cells using high content imaging to count fluorescently-labeled

RXRA and PPARG in Bladder Cancer

nuclei. B, kinetic proliferation assay measuring the effect of 100nM modulator

on growth rate over time in UM-UC-9 with graphical representation of percent of

control calculation. Fluorescently labeled nuclei were counted using IncuCyte

Zoom every 2 hours (n= 4 replicates per condition). Data are represented as

mean ± SD.

Figure 5. Cell lines with PPARG activation are dependent on PPARG. A,

PPARG sgRNA’s 3, and 6 knock out PPARG protein in 5637 cells. A, Western

immunoblot of PPARG and loading control VCL. B, Quantification of PPARG

Western blot signal after normalization to VCL, reported as ratio of integrated

fluorescence intensity K counts and was performed using Li-Cor Odyssey

Application Software version 3.0.30 (Li-Cor, Lincoln NE). C-E, CRISPR/Cas9

competition screen to measure relative proliferation of cells harboring sgRNA

targeting PPARG (yellow), non-essential control of PPARG intron (cyan), and

essential control gene KIF11 (red). Cells lines were infected with lentivirus

encoding both fluorescent marker and sgRNA prior to pooling cells for assay.

Cell lines include B, HT-1997 (RXRA p.S427F), C, Cal 29 (PPARG-activated)

and D, SW1710 (not altered, neutral control). Data are represented as POC,

normalized prevalence of test sgRNAs as a percent of the non-essential

PPARG intron control sgRNA (mean ± SD).

Genomic activation of PPARG reveals a candidate therapeutic axis in bladder cancer

Jonathan T Goldstein, Ashton C. Berger, Juliann Shih, et al.

Cancer Res Published OnlineFirst September 18, 2017.

Updated version Access the most recent version of this article at: doi:10.1158/0008-5472.CAN-17-1701

Supplementary Access the most recent supplemental material at: Material http://cancerres.aacrjournals.org/content/suppl/2017/09/16/0008-5472.CAN-17-1701.DC1

Author Author manuscripts have been peer reviewed and accepted for publication but have not yet been Manuscript edited.

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Subscriptions Department at [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://cancerres.aacrjournals.org/content/early/2017/09/22/0008-5472.CAN-17-1701. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.